Patent literatures 1 and 2 disclose, as a kind of feature selection technique of selecting some features to be used in machine learning or the like from an input set of features, a technique focusing the relevance of features to reduce the calculation cost of learning/identification or the like. However, since all feature combinations are directly evaluated, the calculation cost of feature candidate search is high, and appropriate feature selection cannot be done in polynomial time.
On the other hand, non-patent literatures 1, 2, and 3 disclose a method of efficiently selecting features by evaluating the redundancy between features (in other words, low redundancy) in addition to the relevance of features.